I built an API for easy Email, Webhook and 2FA testing

Hacker News

Hey HN folks, I wanted to showcase and get some feedback on a new product I've been working on over the last few months. It's something I often wished existed to help QA folks with robust automation testing and because I didn't quite like anything that was already out there I built https://msgdrop.io which is an easy to use RESTful API for Email, Webhook and two-factor auth testing. Key features include: - Disposable email addresses from an API - Accessing an inbox through an API - Webhook URLs for testing - Enrol and generate 2FA codes from an API Msgdrop operates its own mail server which means that you don't have to configure a fake SMTP server in order to test mail. Msgdrop works for everyone, including customers who use services such as Mailgun, SendGrid or Resend. Your software sends real emails to actual addresses, and your tests can query these inboxes via HTTP API calls. Additional features include: - Spam testing - Spam scoring - Testing of email attachments - URL auto-discovery - and many more For 2FA testing, you can submit OTP details (e.g. the TOTP secret) or a QR code image to our API in order to enrol, then generate verification codes through the same API - similar to using an app on a phone. I look forward to questions and feedback.

Visit product View on Hacker NewsAug 19, 2024

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Product HuntOn track for Day 1 leaderboard · Strong signals: new, inbox, email · Missing: mac, agents, macos

86%86% predicted probability of success on Product Hunt, based on ML models trained on real launch data.

best fitHighest predicted score across all platforms for this description.

Indie HackersFits the IH revenue-focused audience · Strong signals: including · Missing: supports, reddit linkedin, podcasting

79%79% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.

Hacker NewsStrong engagement from HN community · Strong signals: exist, io, including · Missing: https docs, excited, just released

53%53% predicted probability of success on Hacker News, based on ML models trained on real launch data.

nativeThis product was originally launched on this platform.

TrustMRRLess likely to generate early MRR · Strong signals: month · Missing: mobile apps, ios, personal

45%45% predicted probability of success on TrustMRR, based on ML models trained on real launch data.

AppSumoMay struggle as an AppSumo deal · Strong signals: calls · Missing: plus, platform, intuitive

35%35% predicted probability of success on AppSumo, based on ML models trained on real launch data.

Acquire.comPre-revenue stage for this audience · Missing: arr, mrr, revenue

18%18% predicted probability of success on Acquire.com, based on ML models trained on real launch data.

BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto

0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

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